Thoracic Society of Australia and New Zealand (TSANZ) Is Abrogating Its Leadership Role in Asia-Pacific.Respirology (Carlton, Vic.) • January 05, 2025
Philip Bardin, Christine Mcdonald, Debra Sandford, Gregory King, Christine Jenkins, Paul Reynolds
Background and Objectives
The Hazelwood Health Study was set up to study long-term health effects of a mine fire that blanketed residents of the Latrobe Valley with smoke for 45 days in 2014. The Respiratory Stream specifically assessed the impact of fine particulate matter <2.5 μm diameter (PM2.5) exposure from mine fire smoke on lung health. The multiple breath nitrogen washout (MBW) test assesses ventilation heterogeneity, which may detect sub-clinical airways dysfunction not identified using standard tests such as spirometry. This analysis assessed the association of PM2.5 exposure with measures of ventilation heterogeneity.
Methods
Exposed (Morwell) and unexposed (Sale) participants were recruited 3.5–4 years after the fire from those who had participated in an Adult Survey. MBW was performed to measure lung clearance index (LCI), functional residual capacity (FRC), acinar (Sacin) and conductive (Scond) ventilation heterogeneity. PM2.5 exposure was estimated with emission and chemical transport models. Multivariable linear regression models were fitted controlling for confounders.
Results
We recruited 519 participants. MBW tests were conducted on 504 participants with 479 acceptable test results (40% male; 313 exposed, 166 unexposed). Exposure to mine fire-related PM2.5 was associated with increasing Scond (β = 1.57/kL, 95%CI: 0.20–2.95, p = 0.025), which was comparable to the estimated effect on Scond of 4.7 years of aging. No other MBW outcomes were statistically different.
Conclusion
Increasing exposure to PM2.5 was associated with increased ventilation heterogeneity in the conductive region of the lungs 4 years after the event.
Mechanisms underlying the roles of leukocytes in the progression of cystic fibrosis.Experimental Lung Research • November 15, 2024
Patrick Asare, Minnu Jayapal, Andrew Tai, Suzanne Maiolo, Sally Chapman, Judith Morton, Emily Hopkins, Paul Reynolds, Sandra Hodge, Hai Tran
Recent advances in cystic fibrosis (CF) treatments have led to improved survival, with life expectancy for Australians living with CF at 57yo. As life expectancy improves, long-term cardiovascular disease risk factors (as for the general population) will become an issue in these patients. We hypothesized that increased leukocyte expression of vasoconstriction and pro-fibrotic mediators may contribute to CF severity in adults with CF. We recruited 13 adult and 24 pediatric healthy controls, and 53 adults and 9 children living with CF. Leukocyte expression/release of endothelin-1 (ET1) and members of the TGF-β/Smad signaling were measured by multifluorescence quantitative confocal microscopy, Western blotting, ELISA, and real-time quantitative polymerase chain reaction. The association between plasma ET1 levels and lung function was assessed. Leukocytes from adults living with CF expressed higher ET1 levels (p = 0.0033), and TGF-β (p = 0.0031); the phosphorylation ratio increased for Smad2/3 (p = 0.0136) but decreased for Smad1/5/8 (p = 0.0007), vs. control subjects. Plasma ET1 levels were significantly increased in adults with CF with FEV1<50% (p = 0.002) vs. controls, and adults with CF with normal lung function. The release of ET1 in adult plasma inversely correlated with CF severity (-0.609, p = 0.046). Our data indicates that upregulated ET1 and TGF-β/Smad signaling in leukocytes may contribute to CF severity, highlighting the need for further investigations into their impact on the clinical outcomes of people living with CF.
Pre-Treatment MMP7 Predicts Progressive Idiopathic Pulmonary Fibrosis in Antifibrotic Treated Patients.Respirology (Carlton, Vic.) • September 25, 2024
Roger Li, Dino B Tan, Chantalia Tedja, Wendy Cooper, Helen Jo, Christopher Grainge, Ian Glaspole, Nicole Goh, Samantha Ellis, Peter M Hopkins, Christopher Zappala, Gregory Keir, Paul Reynolds, Sally Chapman, E Walters, Darryl Knight, Svetlana Baltic, Huijun Chih, Tamera Corte, Yuben Moodley
Objective: Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with a poor prognosis. Antifibrotics slow the decline of pulmonary function after 12-months, but limited studies have examined the role of circulatory biomarkers in antifibrotic treated IPF patients.
Methods: Serum from 98 IPF participants, from the Australian Idiopathic Pulmonary Fibrosis Registry were collected at four time-points over 1 year post-antifibrotic treatment and analysed as two separate cohorts. Patients were stratified as progressive, if they experienced ≥ 10% decline in FVC or ≥ 15% decline in DLCO or were deceased within 1 year of treatment initiation: or otherwise as stable. Ten molecules of interest were measured by ELISAs in patient serum.
Results: Baseline MMP7 levels were higher in progressive than stable patients in Cohort 1 (p = 0.02) and Cohort 2 (p = 0.0002). Baseline MMP7 levels also best differentiated progressive from stable patients (Cohort 1, AUC = 0.74, p = 0.02; Cohort 2, AUC = 0.81, p = 0.0003). Regression analysis of the combined cohort showed that elevated MMP7 levels predicted 12-month progression (OR = 1.530, p = 0.010) and increased risk of overall mortality (HR = 1.268, p = 0.002). LASSO regression identified a multi-biomarker panel (MMP7, ICAM-1, CHI3L1, CA125) that differentiated progression more accurately than MMP7 alone. Furthermore, GAP combined with MMP7, ICAM-1, CCL18 and SP-D was more predictive of 3-year mortality than GAP alone.
Conclusions: MMP7 along with a multi-biomarker and GAP panel can predict IPF progression and mortality, with the potential for optimising management.
Availability and Practice Patterns of Videolaryngoscopy and Adaptation of Apneic Oxygenation in Pediatric Anesthesia: A Cross-Sectional Survey of Pediatric Anesthesiologists.Paediatric Anaesthesia • June 22, 2024
Wenyu Bai, Prabhat Koppera, Yuan Yuan, Graciela Mentz, Bridget Pearce, Megan Therrian, Paul Reynolds, Sydney E Brown
Background: Videolaryngoscopy (VL) and apneic oxygenation are highly recommended and increasingly used in pediatric anesthesia practice; yet, availability, use in recommended clinical settings (e.g., neonates, airway emergencies, and out-of-operating-room tracheal intubation), and the association of VL availability with how pediatric anesthesiologists define difficult intubation have not been explored.
Methods: An electronic survey was distributed to the members of several international pediatric anesthesia societies to examine the availability and practice patterns of VL and to explore the criteria used to define a difficult tracheal intubation in children in the context of VL.
Results: The response rate was 12.9%. VL was reported to be "most likely available" in main pediatric operating rooms and offsite locations 93% and 80.1% of the time, respectively. Fifty-seven percent of participants would select VL first when anticipating a difficult tracheal intubation; nearly 30% of respondents would choose direct laryngoscopy first and VL as a backup in this scenario. One-third of subjects would select VL as their first choice for nonoperating room (non-OR) emergency tracheal intubation and for premature or newborn infants, regardless of anticipated difficulty with intubation. Thirty percent of subjects reported using apneic oxygenation during difficult laryngoscopy. Institutional VL availability was not associated with how providers defined difficult tracheal intubation.
Conclusions: VL is highly available, but the adoption of VL and apneic oxygenation for managing difficult tracheal intubation was lower than expected, given recent recommendations by pediatric anesthesia societies. There was heterogeneity in how difficult intubation was defined, resulting in a possible patient safety risk.
Prognostication in patients with idiopathic pulmonary fibrosis using quantitative airway analysis from HRCT: a retrospective study.The European Respiratory Journal • May 01, 2024
Yang Nan, Felder Federico, Stephen Humphries, John Mackintosh, Christopher Grainge, Helen Jo, Nicole Goh, Paul Reynolds, Peter M Hopkins, Vidya Navaratnam, Yuben Moodley, Haydn Walters, Samantha Ellis, Gregory Keir, Chris Zappala, Tamera Corte, Ian Glaspole, Athol Wells, Guang Yang, Simon Walsh
Background: Predicting shorter life expectancy is crucial for prioritizing antifibrotic therapy in fibrotic lung diseases, where progression varies widely, from stability to rapid deterioration. This heterogeneity complicates treatment decisions, emphasizing the need for reliable baseline measures. This study focuses on leveraging artificial intelligence model to address heterogeneity in disease outcomes, focusing on mortality as the ultimate measure of disease trajectory.
Methods: This retrospective study included 1744 anonymised patients who underwent high-resolution CT scanning. The AI model, SABRE (Smart Airway Biomarker Recognition Engine), was developed using data from patients with various lung diseases (n=460, including lung cancer, pneumonia, emphysema, and fibrosis). Then, 1284 high-resolution CT scans with evidence of diffuse FLD from the Australian IPF Registry and OSIC were used for clinical analyses. Airway branches were categorized and quantified by anatomic structures and volumes, followed by multivariable analysis to explore the associations between these categories and patients' progression and mortality, adjusting for disease severity or traditional measurements.
Results: Cox regression identified SABRE-based variables as independent predictors of mortality and progression, even adjusting for disease severity (fibrosis extent, traction bronchiectasis extent, and ILD extent), traditional measures (FVC%, DLCO%, and CPI), and previously reported deep learning algorithms for fibrosis quantification and morphological analysis. Combining SABRE with DLCO significantly improved prognosis utility, yielding an AUC of 0.852 at the first year and a C-index of 0.752.
Conclusions: SABRE-based variables capture prognostic signals beyond that provided by traditional measurements, disease severity scores, and established AI-based methods, reflecting the progressiveness and pathogenesis of the disease.
